• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.19-31
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• 2023

The importance of barrier free is being highlighted worldwide. This study attempted to identify barrier-free research trends using text mining. Through this, it was intended to help with research and policies to create a barrier free environment. The analysis data is 227 papers published in domestic academic journals from 1996 when barrier free research began to 2022. The researcher converted the title, keywords, and abstract of an academic thesis into text, and then analyzed the pattern of the thesis and the meaning of the data. The summary of the research results is as follows. First, barrier-free research began to increase after 2009, with an annual average of 17.1 papers being published. This is related to the implementation guidelines for the barrier-free certification system that took effect on July 15, 2008. Second, results of barrier-free text mining i) As a result of word frequency analysis of top keywords, important keywords such as barrier free, disabled, design, universal design, access, elderly, certification, improvement, evaluation, and space, facility, and environment were searched. ii) As a result of TD-IDF analysis, the main keywords were universal design, design, certification, house, access, elderly, installation, disabled, park, evaluation, architecture, and space. iii) As a result of N-Ggam analysis, barrier free+certification, barrier free+design, barrier free+barrier free, elderly+disabled, disabled+elderly, disabled+convenience facilities, the disabled+the elderly, society+the elderly, convenience facilities+installation, certification+evaluation index, physical+environment, life+quality, etc. appeared in a related language. Third, as a result of the CONCOR analysis, cluster 1 was barrier-free issues and challenges, cluster 2 was universal design and space utilization, cluster 3 was Improving Accessibility for the Disabled, and cluster 4 was barrier free certification and evaluation. Based on the analysis results, this study presented policy implications for vitalizing barrier-free research and establishing a desirable barrier free environment.

• Journal of the Korean Society of Food Culture
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• v.23 no.2
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• pp.293-300
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• 2008

It determines Chinese addiction to piquancy that the Chinese traditional food production laid excessively particular stress on agriculture coming into being long before in the history and the state of Chinese food living was that the people were very difficult to live. The history of Chinese addiction to piquancy could be traced back to prehistory. And in Chinese “hot” is separated from “peppery” and it refers in particular to the piquancy more than general peppery. The character of “Hot” appeared after Han Dynasty in Chinese. Capsicum was brought to China from the sea in the middle of Ming Dynasty. Then it surpassed the formers soon and became the most popular and addictive piquancy food in China. Capsicum has many names in China, such as “$F{\bar{a}}nji{\bar{a}}o$”, “$H{\bar{a}}iji{\bar{a}}o$”, “$L{\grave{a}}ji{\check{a}}o$”, “$L{\grave{a}}h{\breve{u}}$”, “$L{\grave{a}}zi$”, etc., and they indicate the geographical and humanistic character of the distribution. (eight books on preserving one’s health) is the earliest history record about capsicum in existent Chinese history record that was finished in 1591. In this article the author puts new opinion forward on the record in this book. It is because the hottest piquancy of capsicum, capsicum’s better adaptability and low cost to plant combine with Chinese piquancy addiction at large that capsicum can replace the status of pepper and other traditional peppery flavorings soon and cause worldwide attention to the Chinese piquancy addiction finally. The human common characters of unchangeable inertia, depending to fully grow addiction and aggrieved delight are the most important reasons to cause piquancy addiction that has formed a custom through long-repeated practice and this custom do not change with condition change. The unbalanced spread process of capsicum in China shows that the region is poorer and the addictive degree is deeper.

• (The) Research of the performance art and culture
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• no.23
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• pp.37-61
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• 2011

The Noh(能) performance is a traditional drama that represents Japan. The Noh performance was approved in the background of religious thought such as Shintoism(神道), Buddhisms(佛敎), and Syugendo(修驗道). Especially, the influence from Shugendo is large. Shugendo was active in the Middle Ages. Especially, the influence from Shugendo is large. Shugendo was active in the Middle Ages. The Noh was approved while receiving a large influence from Shugendo. It can know the feature of the Shugen(修驗) culture in the Middle Ages through the consideration of . Moreover, the appearance of the training of 'Yamabusi(山伏)' can be seen. "Yamabusi" has not been paid to attention up to now in the research of . And, the focus was appropriated to Yamabusi and it researched in this text. Moreover, the problem of "Chigo(稚子)" is thought through . "Chigo culture" was general in the Middle Ages. It is thought that "Chigo culture" is reflected in . is an Noh performance for the boy named 'Wakamatsu' to enter the mountain and to train. It is because mother's sickness was cured. However, the boy gets sick while it is training. It was dropped to the valley according to the law of Shugendo, and it died. However, it revives by the Yamabusi's prayers. 'Taniko' is to drop to the valley and to bury it when the Yamabusi gets sick while lived. The title of the Noh originated in here. has elements of history, content of training of Shugendo, "Filial piety", and the Chigo culture, etc. These are features of the culture in the Middle Ages. It is not only a sad content though this is a content of the cruel remainder. It is because of the revival though waited rapidly at the end. As for the difficulty of training is drawn in the round, and the appearance of the training at that time is understood well. The essence of Shugendo is to train in the mountain. Supernatural power can be obtained through training. Moreover, it was thought that it was able to be newly reborn through training. The leading part of Shugendo is an Yamabusi. The Yamabusi took an active part in not only the mountain but also the village. The Yamabusi is ordinary people's lives and because the relation is deep, an important factor it knows the folk customs of Japan. The word 'Chigo' is not written in . However, a spectator at that time is 'Chigo' Wakamatsu and is already sure to have understood 'Chigo'. Because everyone knew the Chigo culture in the Middle Ages. A religion at that time and knowledge of the society are necessary to understand the play of Nho well.

• Sim-seong Yeon-gu
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• v.28 no.1
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• pp.50-87
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• 2013

C. G. Jung believed that universal and basic condition of human's Unconscious comes out from Märchen or mythology. We can easily experience these universality of human nature in dreams. Therefore, It is very important to interpret mythogens that appear in myths and märchen in analytical psychology to understand these 'big dreams' which could be seen in clinical practice. As I was interested in interpreting myths in analytic psychology, I tried to find universality of archetypes in Korea's traditional folk tales and took note of the birth myth of Hyeokgeose, the founder of Shilla dynasty, while examining the chater of the Unsual in history in the Heritage of the Three Kingdoms. Shilla was founded earlier than two other countries, but it was located in the very south of the Korean Peninsula, and it was behind times in politically, militarily, and culturally compare to Goguryeo and Baekje. However, Shilla achieved unifying the Three Kingdoms and it lasted 1000 years, the longest unified history in Korean history. I tried to examine archetypes in the birth myth if there are any backgrounds that are related to finding a Shilla Kingdom. It is noted that myth of the founder of Korean Peninsula's small Kingdom Shilla has complete story from before the birth to birth, birth of spouse, growth, marriage, accession, governing, death, after death, and succession. Symbols such as numbers 1, 3, 5, 6, 7, 13 and 61, various azimuthes including north, west, south, east, and central, animals like tiger, white horse, hen, dragon, phoenix, and snakes, natures like main symbol egg, rock, gourd, lightening, spring water, stream, tree, forest, mountain, iron and goddess-image like seon-do Holy Mother gradually appears in the myth. These symbols could show a meaning of human experience such as birth of Conscious, growth and development of paternal and maternal love, and story of regeneration and extinction. Moreover, It could be seen as these progress eternally continues in next generation. I have found out that a word, a sentence or stories that looks meaningless in myth revealed its true symbolical meaning. In addition, interaction between Unconscious and Conscious repeats in different forms, and expressed in layered.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.